Triple

T13347999
Position Surface form Disambiguated ID Type / Status
Subject Chubu tourism area E318005 entity
Predicate hasFamousSite P1098 FINISHED
Object Takayama E501071 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Takayama | Statement: [Chubu tourism area, hasFamousSite, Takayama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Takayama
Context triple: [Chubu tourism area, hasFamousSite, Takayama]
  • A. Takayama chosen
    Takayama is a historic mountain city in Japan’s Gifu Prefecture, known for its well-preserved Edo-period streets, traditional wooden houses, and proximity to the Japanese Alps.
  • B. Matsumoto
    Matsumoto is a historic city in central Japan best known for its well-preserved Matsumoto Castle and as a gateway to the scenic Japanese Alps.
  • C. Kōka
    Kōka is a city in Shiga Prefecture, Japan, historically famous as the home of the Kōga ninja tradition.
  • D. Kusatsu
    Kusatsu is a Japanese city in Shiga Prefecture known as a regional commercial hub and transportation crossroads near Lake Biwa.
  • E. Kitanagoya
    Kitanagoya is a city in central Japan known as a residential and commercial suburb within the Nagoya metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8b28e48190a23194e03a74b41b completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a055ba649d08190bb093403ebe90d38 completed May 14, 2026, 5:20 a.m.
Created at: April 9, 2026, 9:31 p.m.